具交換性二元存活函數之估計
Date Issued
2004
Date
2004
Author(s)
花雅惠
DOI
zh-TW
Abstract
Abstract
Multiple event data are frequently encountered in many medical researches. For example, the data arise from studying the ages of onset of twin for a specific chronic disease, which form parallel data. While observing the gap time between the episodes of rehospitalization of schizophrenia patients, one encountered serial event data. The outcomes of interest are the bivariate survival times of twin for the parallel data, and the bivariate gap times for the serial event data. In both types of data, it may be sensible to assume that the bivariate survival function is exchangeable. Under the exchangeability of the bivariate survival function, we can modify the estimators proposed by Lin and Ying (1993) and Lin et al. (1999). Two classes of nonparametric estimators of the bivariate (gap time) survival function are developed. Simulation is presented to investigate the finite sample performance of the proposed estimators for parallel and serial event data.
Subjects
二元存活函數
具交換性
復發事件
群集資料
Clayton model
無母數估計
bivariate survival function
nonparametric estimation
recurrent event
exchangeability
parallel data
Type
thesis
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